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Record W1823657563 · doi:10.1002/bsl.2141

An Examination of “Don't Know” Responses in Forensic Interviews with Children

2014· article· en· W1823657563 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBehavioral Sciences & the Law · 2014
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsNeed to knowPsychologyAffect (linguistics)Human factors and ergonomicsSuicide preventionForensic sciencePoison controlSocial psychologyChild abuseInjury preventionMedicineMedical emergencyComputer securityComputer scienceCommunication

Abstract

fetched live from OpenAlex

Most experimental studies examining the use of pre-interview instructions (ground rules) show that children say "I don't know" more often when they have been encouraged to do so when appropriate. However, children's "don't know" responses have not been studied in more applied contexts, such as in investigative interviews. In the present study, 76 transcripts of investigative interviews with allegedly abused children revealed patterns of "don't know" responding, as well as interviewers' reactions to these responses. Instructions to say "I don't know" when appropriate did not affect the frequency with which children gave these responses. Interviewers rejected "don't know" responses nearly 30% of the time, and typically continued to ask about the same topic using more risky questions. Children often answered these follow-up questions even though they had previously indicated that they lacked the requested information. There was no evidence that "don't know" responses indicated reluctance to talk about abuse. Implications for forensic interviewers are discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.494

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.077
GPT teacher head0.347
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it